The video surveillance company uses Oracle Cloud Infrastructure’s superior price-performance to cost-effectively expand its elaborate cloud footprint.
“Since moving off AWS, we have quadrupled our data footprint while reducing our costs by 40%. We use 33% less GPU-compute capacity on OCI than AWS.”
Tango Eye converts surveillance video into actionable insights for the retail industry. Artificial intelligence (AI) algorithms use terabytes of daily footage data from closed-circuit TV cameras to uncover customers’ shopping patterns. These patterns help managers supervise stores better—they can assess KPI levels for customer footfall, maintain store compliance, and ensure merchant safety.
Tango Eye did not want to use on-premises infrastructure and saw advantages with managed services provided by cloud vendors. Its initial product was built on Amazon Web Services, but the company found that Amazon’s scaling and pricing did not meet expectations.
Oracle Cloud Infrastructure provides good, timely support and architectural assistance. We are much better equipped to scale exponentially.
Why Tango Eye Chose Oracle
After working with AWS for a year, Tango Eye began to migrate all its applications to Oracle CIoud Infrastructure (OCI) to take advantage of higher performance with lower cost. The company considered colocation services and other cloud vendors. But the Oracle for Startups program and managed services from OCI such as OCI Streaming, Oracle Functions, OCI Events, OCI Object Storage, and OCI Compute—CPU and GPU—tilted the balance in Oracle’s favor.
Engineers saw significant benefits in using Oracle-managed services for event streaming and serverless functions, which offload the burden of maintaining these platforms. This allowed engineers to focus on rapid application development.
Today, OCI Streaming serves as a low-maintenance publish-subscribe messaging system for various microservices. Oracle Functions executes serverless jobs without any engineering oversight. In addition, lifecycle policies for OCI Object Storage automatically archive and purge data, reducing costs without diminishing the value of Tango Eye’s AI-based analytics.
Tango Eye’s monthly burn rate on AWS was simply too high, but the team wanted to take advantage of the cloud-delivery model. After a thorough analysis of Oracle Cloud Infrastructure’s capabilities, the company decided that all of the necessary components of its architecture could be implemented more cost-effectively on OCI.
On AWS, Tango Eye managed daily data volumes of 1 TB. Since moving to OCI, while daily data volumes have increased by 3X to 4X, the number of GPU-based compute instances has decreased by 33% as a result of OCI’s higher performance and Tango Eye’s code enhancements.
In addition, OCI’s compartment-level isolation, a feature not available in AWS, provides its cloud operators with the necessary controls to efficiently manage deployments across DevTest, quality assurance (QA), and production.